Decision Analysis for Management Judgment - Paul Goodwin

Jul 31, 2026

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A comprehensive introduction to decision analysis for management judgment, guiding readers through complex choices under multiple objectives, uncertainty, and risk. Covers value trees, SMART, alternatives such as AHP, and utility theory for both monetary and non-monetary attributes. Develops probability foundations, decision trees and influence diagrams, simulation and Monte Carlo methods, and Bayes’ theorem for revising judgments. Addresses heuristics and biases, elicitation of probabilities, structured risk management, group decision processes, resource allocation and negotiation, decision framing and cognitive inertia, and scenario planning combined with decision analysis, including AI decision-support.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages645

Reading Time27 h 5 min

AccessFree to download

1 Introduction

2 How people make decisions involving multiple objectives

3 Decisions involving multiple objectives: SMART

4 Decisions involving multiple objectives: alternatives to SMART

5 Introduction to probability

6 Decision-making under risk

7 Decision trees and influence diagrams

8 Applying simulation to decision problems

9 Revising judgments in light of new information

10 Heuristics and biases in probability assessment

11 Methods for eliciting probabilities

12 Structured risk management

13 Decisions involving groups of individuals

14 Resource allocation and negotiation problems

15 Decision framing and cognitive inertia

16 Scenario planning: a way of dealing with uncertainty

17 Combining scenario planning with decision analysis

18 Alternative decision-support systems and the role of AI

Table of Contents Cover Table of Contents Title Page Copyright Dedication Foreword to First Edition Preface Accompanying website at www.wiley.com/go/goodwin6e 1 Introduction Complex decisions The role of decision analysis Good and bad decisions and outcomes Applications of decision analysis Our own consultancy-based case examples of scenario planning Overview of the book References 2 How people make decisions involving multiple objectives Heuristics used for decisions involving multiple objectives Other characteristics of decision-making involving multiple objectives Summary Exercises References 3 Decisions involving multiple objectives: SMART Basic terminology An office location problem An overview of the analysis Constructing a value tree Measuring how well the options perform on each attribute Determining the weights of the attributes Aggregating the benefits using the additive model Trading benefits against costs Sensitivity analysis Theoretical considerations Conflicts between intuitive and analytic results Summary Exercises References 4 Decisions involving multiple objectives: alternatives to SMART Smarter Even Swaps Even Swaps versus SMART The analytic hierarchy process Performing AHP calculations by hand The axioms of theAHP TheAHP versus SMART MACBETH Summary Exercises References 5 Introduction to probability Outcomes and events Approaches to probability Mutually exclusive and exhaustive events Complementary events Marginal and conditional probabilities Independent and dependent events The multiplication rule Probability trees Probability distributions Expected values The axioms of probability theory Summary Exercises References 6 Decision-making under risk The maximin criterion The expected monetary value criterion Limitations of the EMV criterion Single-attribute utility Interpreting utility functions Utility functions for non-monetary attributes The axioms of utility More on utility elicitation Limitations of applying utility Multi-attribute utility Summary Exercises References 7 Decision trees and influence diagrams Constructing a decision tree Determining the optimal policy Decision trees and utility Decision trees involving continuous probability distributions Assessment of decision structure Eliciting decision-tree representations Summary Exercises References 8 Applying simulation to decision problems Monte Carlo simulation Applying simulation to a decision problem Applying simulation to investment decisions Modeling dependence relationships Summary Exercises References 9 Revising judgments in light of new information Bayes’theorem The effect of new information on the revision of probability judgments Applying Bayes’theorem to a decision problem Assessing the value of new information Summary Exercises References 10 Heuristics and biases in probability assessment Heuristics and biases The representativeness heuristic The anchoring and adjustment heuristic Is human probability judgment really so poor? Summary Exercises References 11 Methods for eliciting probabilities Issues with verbal probability expressions Coherence in probability judgments Two barriers to improving probability assessments through learning Preparing for probability assessment Consistency and coherence checks Assessing the validity of probabilities Assessing probabilities for very rare events Communicating probability estimates Summary Exercises References 12 Structured risk management The Two Valleys Company Summary Exercises References 13 Decisions involving groups of individuals Mathematical aggregation Aggregating judgments in general Aggregating probability judgments Aggregating preference judgments Unstructured group processes The Delphi method Prediction markets

FAQs

What is decision analysis used for in management judgment?

It supports good decisions by structuring and analyzing complex choices, especially when multiple objectives, uncertainty, and risk affect outcomes.

How does SMART help with decisions involving multiple objectives?

SMART builds a value tree, measures option performance on each attribute, assigns attribute weights, aggregates benefits, and uses methods like sensitivity analysis to explore trade-offs.

How are probabilities revised when new information becomes available?

Bayes’ theorem updates probability judgments, and the approach also assesses the value of the new information for the decision.

Jul 31, 2026

Upload by Aurora